Machine Learning Engineer

Bynder goes far beyond managing digital assets. Our AI-powered digital asset management platform enables teams to conquer the chaos of proliferating content, touch points, and relationships in order to thrive.

With intuitive, AI-powered solutions that enhance content creation, simplify asset discovery, and maximize the value of every asset, we are the brand ally that unifies and transforms the creation and sharing of assets—inspiring teams, delighting customers, and elevating businesses.

Join our global team of 600+ ‘Byndies’ and contribute to shaping the future of digital asset management! As a leader in the industry, our AI capabilities empower over 1.7M users across 4,000+ organizations, including Spotify, Puma, Five Guys and Icelandair to work smarter with their content. With a commitment to innovation and a presence in eight offices worldwide, Bynder offers a dynamic environment where you can make a real impact.

Ready to grow your career by helping the world's leading brands create exceptional content experiences and thrive? Explore this opportunity and apply now to join our talented team.

Bynder AI Labs is our dedicated AI innovation team. We’re a small, high-impact group of AI experts responsible for researching, prototyping, and shipping the next generation of AI-powered capabilities for Bynder’s platform. We’ve already delivered features like AI Search and AI Agents for content enrichment, governance, compliance and transformation.

We sit at the intersection of cutting-edge AI research and practical product development. Our job is to figure out what’s possible and make it real. We are looking for a Machine Learning Engineer who wants to define what comes next.

• Design, build, and deploy AI-powered features for Bynder’s DAM platform, focusing on content discoverability, automation, and intelligent workflows.
• Architect and implement solutions using AWS AI services (Bedrock, Sage Maker, Lambda) and large language model APIs.
• Build and optimize embedding-based systems for AI search, semantic retrieval, and content recommendation.
• Develop agentic AI workflows that automate complex tasks such as asset enrichment, tagging, transformation, and compliance checking.
• Create production-quality prototypes and proof-of-concepts that demonstrate the value of new AI capabilities to stakeholders.
• Stay current with the rapidly evolving AI landscape and bring fresh ideas and techniques to the team.
• Collaborate with the broader engineering organization to ensure smooth handoff of prototypes into production systems.
• Collaborate directly with product stakeholders and end-users to validate AI prototypes and gather feedback for successful delivery

• Minimum of 3+ years of experience in Machine Learning Engineering, AI Engineering, Data Science, or a similar role.
• Strong understanding of how large language models work: transformer architectures, attention mechanisms, tokenization, embeddings, and inference pipelines.
• Hands‑on experience with cloud AI services, particularly AWS (Bedrock, Sage Maker, Lambda).
• Practical experience building systems with embeddings and vector databases for semantic search or retrieval‑augmented generation (RAG).
• Familiarity with agentic AI frameworks (e.g., Lang Chain, Lang Graph, CrewAI, or similar) and understanding of agent architectures including planning, memory, and tool use.
• Strong software engineering fundamentals:
  Python, REST APIs, Git, Docker, and CI/CD.
• Solid foundation in mathematics: linear algebra, probability, statistics, and optimization. Understanding of classical ML algorithms and when they apply.
• Bachelor’s degree in Computer Science, AI, Mathematics, Physics, or a related field.

• Master’s degree or PhD in a relevant field.
• Experience with prompt engineering, context engineering, and LLM evaluation frameworks.
• Knowledge of MLOps practices: model monitoring, A/B testing, and deployment pipelines for AI features.
• Experience with computer vision or image/video processing (highly relevant to our DAM domain).
• Proficiency with AI‑assisted coding tools and workflows (Git Hub Copilot, Cursor, Claude Code,…